Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Canvas-LMS-MCP/canvas-teacher-mcp --skill grade-nbgit clone --depth 1 https://github.com/Canvas-LMS-MCP/canvas-teacher-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/canvas-lms-mcp/canvas-teacher-mcp/grade-nb)<a href="https://agentmods.dev/skills/canvas-lms-mcp/canvas-teacher-mcp/grade-nb"><img src="https://agentmods.dev/badge/skills/canvas-lms-mcp/canvas-teacher-mcp/grade-nb/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/canvas-lms-mcp/canvas-teacher-mcp/grade-nb"><img src="https://agentmods.dev/badge/skills/canvas-lms-mcp/canvas-teacher-mcp/grade-nb.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00142 | $0.04538 |
| Opus 5 | $0.00071 | $0.02269 |
| Sonnet 5 | $0.00028 | $0.00908 |
| Haiku 4.5 | $0.00014 | $0.00454 |
Grade A, and why
grade-nb scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
grade-nb — notebook + revision-history inspection (sub-skill of grade)
Invoked FROM skills/grade/SKILL.md when a submission IS (or is designated) a Colab/Jupyter notebook —
then it is REQUIRED, not optional (do not eyeball an NB on the bare general path). It runs INSIDE
the full grade spine — it does NOT replace or shortcut it:
Step 0 (scope: needs-grading queue + late/waivers) → Stage A (the ENGINE gathers via
attachments.read → graders/nb.py: notebook{cells, pinned revisions} + body/all_text, then
nb_inspect.resolve_tasks region completeness + revision_progression/score_revision process →
emitted as review_content) → Stage B (ALL general rules — §0Z FULL read, instructions rubric,
per-below-max reason, comment_render — the AI SCORES from review_content: comp per-problem 1/N,
rev process, refl from the reflection location) → report → self-challenge → POST. It supplies the
NB-specific DETAIL within Stage A + Stage B; it NEVER skips Step 0 or the general Stage-B rules. Policy
homes: GRADING.md Part C + GradingEngine/NbInspect.md (this file orders them into steps — it does
not re-decide policy).
⛔ Two rules that made past NB grading wrong (do NOT repeat)
- §0Z — never truncate. Read the WHOLE notebook, every cell source + output, IN FULL. The engine
lib/nb_inspect.load_notebookreads the entire file (raises if it can't) so nothing is sliced. - DIFF vs the template — never regex the merged notebook. Judge only the student-ADDED cells
(
template_added_cells(student, template)). The template's own example<img>, theplaceholder, and provided task cells will fool a merged scan.
Fetching = the ENGINE's job (grade-nb never calls gws)
attachments.read(submission) (called by graders/nb.py) fetches the notebook in ONE read →
["notebook"] = {drive_id, accessible, cells, revisions(pinned)} PLUS body_text / all_text
(where the Reflection lives). grade-nb / any grader NEVER calls gws directly (Attachments.md;
engine selftest greps for gws/HTTP outside attachments.py → STOP). The 2026-07-03 gws-cwd
detail lives INSIDE attachments.py, not here.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 227 lines · 142 tokens per session scan A fd101eb00f4b
grade-nb is a skill published in the GitHub repository Canvas-LMS-MCP/canvas-teacher-mcp (1 stars, last pushed 27d ago), licensed MIT. It adds 142 tokens to every session and 4,538 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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